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Record W7098225437

www.mdpi.com/journal/ijerph Article Drinking Water Quality Guidelines across Canadian Provinces and Territories: Jurisdictional Variation in the Context of Decentralized Water Governance

2014· article· en· W7098225437 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Corporate governanceWater qualityPublic healthQuality (philosophy)Water industryWater supplyCompliance (psychology)
DOInot available

Abstract

fetched live from OpenAlex

Abstract: This article presents the first comprehensive review and analysis of the uptake of the Canadian Drinking Water Quality Guidelines (CDWQG) across Canada’s 13 provinces and territories. This review is significant given that Canada’s approach to drinking water governance is: (i) highly decentralized and (ii) discretionary. Canada is (along with Australia) only one of two Organization for Economic Cooperation and Development (OECD) member states that does not comply with the World Health Organization’s (WHO) recommendation that all countries have national, legally binding drinking water quality standards. Our review identifies key differences in the regulatory approaches to drinking water quality across Canada’s 13 jurisdictions. Only 16 of the 94 CDWQG are consistently applied across all 13 jurisdictions; five jurisdictions use voluntary guidelines, whereas eight use mandatory standards. The analysis explores three questions of central importance for water managers and public health officials: (i) should standards be uniform or variable; (ii) should compliance be voluntary or legally binding; and (iii) should regulation and oversight be harmonized or delegated? We conclude with

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.263
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.017
Science and technology studies0.0020.003
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0320.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.264
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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Same topicBotany, Ecology, and Taxonomy StudiesFrench-language works237,207